Quantitative Developer-4

Job Overview

JOB DETAILS

REQUIREMENTS

• Education: Master’s or Ph.D. in Computer Science, Mathematics, Financial Engineering, or a related quantitative field from a reputed institution.
• Overall 9-15+ years of IT experience
• Must have at least 5-8+ years of progressive experience in software engineering and quantitative development.
• Strong experience with data processing libraries such as Pandas, Polars, CuML, etc
• Familiarity with cloud big data platforms, particularly Databricks.
• Experience working with large datasets and building scalable data pipelines.
• Proficiency in Python and PySpark (must-have), with hands-on experience in R and Java.
• Domain Knowledge: Solid understanding of financial instruments including securities and derivatives, along with capital markets structure.
• Development Practices: Strong commitment to clean code, adaptive systems, and iterative design using TDD methodologies.
• Able to explain technical strategies and solutions to both technical and business audiences.
• Quick to learn new technologies and quantitative methods.

RESPONSIBILITIES

• Design and implement production-grade code that translates quantitative models into efficient and scalable solutions.
• Work closely with Quantitative Research, Risk, and Equity Portfolio Management teams to support model development and risk analytics.
• Contribute across the software development lifecycle including requirements analysis, coding, testing, and deployment.
• Build solutions using a wide array of technologies including Python, PySpark, R, Java, and cloud-based big data platforms like Databricks.
• Develop in both real-time and batch-oriented architectures.
• Employ Test-Driven Development (TDD) to ensure code quality, scalability, and maintainability.
• Continuously explore and integrate modern technologies and industry best practices into development processes.
• Communicate complex quantitative and technical concepts effectively to non-technical stakeholders.

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